At a Glance
- Tasks: Lead engineering for AI/ML solutions and design production-grade systems.
- Company: Join JPMorganChase, a leader in applied AI technology.
- Benefits: Competitive salary, career growth, and opportunities to work with cutting-edge tech.
- Other info: Collaborative culture with a focus on learning and innovation.
- Why this job: Shape the future of intelligent systems and make a real impact.
- Qualifications: Degree in computer science or equivalent experience; proficiency in Python and system design.
The predicted salary is between 70000 - 90000 £ per year.
Build what's next in applied AI at JPMorganChase - where your work shapes how teams use intelligent systems at scale. You'll lead hands-on engineering for agentic and GenAI capabilities that power the LLM Suite platform. This role offers a mix of deep technical problem-solving, architecture ownership, and collaboration with talented builders. If you enjoy turning ambiguity into reliable production systems, you'll thrive here. Join a team that values craft, security, and learning.
As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. You will own technical direction across architecture, implementation, and operational stability, with a strong focus on secure, high-quality software. You will partner with peers across engineering to identify patterns and improve standards, reliability, and scalability. You will help evolve the platform using modern public cloud services and agentic frameworks. You will contribute to a collaborative culture through communities of practice and emerging-technology events. You will explore and operationalize emerging patterns such as agent-to-agent communication, model context protocols, and agentic orchestration, turning early-stage concepts into scalable, production-ready capabilities.
Job Responsibilities
- Design, develop, and troubleshoot software solutions using creative approaches to solve complex technical challenges
- Write secure, high-quality production code and maintain algorithms that integrate with existing systems
- Create architecture and design artifacts for complex applications, ensuring design constraints are met through delivery
- Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks
- Implement GenAI services leveraging Azure OpenAI models and AWS Bedrock
- Identify hidden problems and patterns in data proactively to improve coding standards and system architecture
- Participate in software engineering communities of practice and events focused on emerging technologies
Required Qualifications, Capabilities, and Skills
- Computer science degree or equivalent practical experience
- Hands-on experience with system design, application development, testing, and operational stability
- Proficiency in Python (FastAPI)
- Experience building microservices and APIs
- Experience with elastic compute, NoSQL databases, and messaging queues
- Strong understanding of the Software Development Life Cycle
- Solid grasp of CI/CD, application resiliency, and security
Preferred Qualifications, Capabilities, and Skills
- Experience implementing GenAI services leveraging Azure OpenAI models and AWS Bedrock
- Proficiency working with large language models and building agents with LangGraph
- Experience developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages
- Experience with containerization
- Knowledge of agent-to-agent (A2A) communication concepts
- Familiarity with Model Context Protocol (MCP)
- Experience with agentic orchestrators, personal AI assistants, or AI skills development
About The Team
Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.
Applied AI ML Lead Engineer - LLM Suite Engineering employer: J.P. Morgan
At JPMorgan Chase, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. As an Applied AI ML Lead Engineer, you'll not only work on cutting-edge technology but also benefit from a supportive environment that encourages continuous learning and professional growth. Our commitment to security, quality, and teamwork ensures that you will thrive while making a meaningful impact in the financial sector.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI ML Lead Engineer - LLM Suite Engineering
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at J.P. Morgan or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to J.P. Morgan.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like J.P. Morgan.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like J.P. Morgan that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Applied AI ML Lead Engineer - LLM Suite Engineering
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at J.P. Morgan.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at J.P. Morgan and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at J.P. Morgan
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If J.P. Morgan uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
